

*Set in CD and open data 

*cd ""
*use  UBCNES_156673_20190107.dta, clear


******** Prepare data ********

*rename S4 ideology 
*rename S5 partyid 
*rename S6 partystrenght
*rename S7 partyid_followup
*rename S9 vote 

*rename J6 polknow1
*rename J7 polknow2
*rename J8 polknow3
*rename J9 polknow4
*rename J10 polknow5
*rename J11 polknow6

*rename S20 unemploy
*rename S21 income
*rename S22 househp
*rename S23 househminor

*rename PARTIDO_L list_partido
*renam MOSTRAR_L listexp
*label drop MOSTRAR_L 
*label define listexp 1 "Direct question" 2 "Short list" 3 "Long list"
*label val listexp listexp

*rename L1 list_directq
*rename L2 list_short
*rename L3 list_long
 
*recode EDUCATION (1/2=1 "low education") (3/4=2 "middle education") (5/7=3 "high education"), gen (education) 

*keep list_short list_long list_directq partyid listexp education sex age income ideology partyid 

*save "Do_they_really_care.dta", replace

use Do_they_really_care.dta, clear 

******** Analysis ********

** Table 1: : Results across different treatment conditions 

* Means comparison List experiment 
mean list_short
mean list_long
di  2.845  -  2.02 // 82,5% consider corruption reason not to vote for candidate of their preferred party
di 100 - 82.5      // 17,5% do not consider corruption a valid reason for not voting a candidate of their preferred party

* Results of direct questions 
tab list_directq  // 22,5% would vote for corrupt politician
            
			 
* Means comparison list experiment for only partisans  			 

mean list_short if partyid!=97
mean list_long if partyid!=97
di 2.70-1.96                  // 74% consider corruption reason not to vote for candidate of their preferred party
di 100 - 74                   // 26% do not consider corruption a valid reason for not voting a candidate of their preferred party

* Results of direct questions with only partisans
 tab list_directq if partyid!=97  //28,27% would vote for corrupt politician


* Test wether difference among short and long list is significant 
recode listexp (1=.), gen(experiment) 
generate experiment1= experiment-2

egen float list1 = rowfirst(list_short list_long)
label variable list1 "Items in list experiment"
mean list1, over(experiment) 

ttest listexp, by(experiment) 


** Table A1: Randomization check: multinomial logit model

recode education (8=.), gen (edu2)
 
mlogit listexp i.sex age i.edu2 income ideology partyid 
  
eststo: mlog listexp i.sex age i.edu2 income ideology partyid 
esttab using Mlogit_listexp2.rtf, nolabel unstack nomti onecell wide noomitted nogap ///
label  nonumbers  ///
starlevels(* 0.05 ** 0.01 *** 0.001) ///
b(2) se(2) sca(chi2 p) obslast /// 
addnote("Note: Dependent Variable: listexperiment. Base category: treated") ///
varlabels(_cons Constant  sex "Gender" age "Age" edu2 "Education" income "income" ideology "ideology" partyid "partisanship")replace 

mlogit  listexp i.sex 
mlogit  listexp age
mlogit  listexp i.edu2
mlogit  listexp  income 
mlogit listexp ideology

recode partyid (1=1 "PP") (2=2 "PSOE") (3=3 "Podemos") (4=4 "C's") (5/97=.), gen (partisans)

mlogit listexp partisans 